diff --git a/w1/README.pdf b/w1/README.pdf
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+# Comparison between C-implemented and R-implemented dual-loop matrix summing function performance
+
+## Running
+
+To run this project, run the following commands:
+
+```bash
+# matrix test
+Rscript mat_tests.R
+```
+
+### Building and running
+
+If you edit the C code, to recompile run:
+
+```bash
+bash make_c.sh
+```
+
+### View Evaluation
+
+To install packages necessary for this .rmd document, run:
+
+```bash
+Rscript install_libs.R
+```
+
+## Evaluation 
+The experiment shows the performance comparison between the R-implemented and C-implemented matrix summing functions 
+for different matrix sizes. As the matrix size increases, the C-implemented function demonstrates significantly 
+better performance compared to the R-implemented function.
+Surprisingly, the speedup remains fairly constant in relative terms, stabilizing at about 4x
+
+
+
+
+> Note: Evaluation script run on an AMD Ryzen 9 7950X3D cpu with enough RAM for all matrix sizes
+
+
+| Matrix size | sum1 run duration (secs) | sum2 run duration (secs) |
+|-------------|---------------------------|---------------------------|
+| 5x5         | 7.152557e-06              | 7.867813e-06              |
+| 10x10       | 9.775162e-06              | 5.00679e-06               |
+| 50x50       | 9.346008e-05              | 8.106232e-06              |
+| 100x100     | 0.0003376007              | 1.955032e-05              |
+| 500x500     | 0.007472992               | 0.001415014               |
+| 1000x1000   | 0.03007007                | 0.005748034               |
+| 5000x5000   | 0.6559205                 | 0.1854615                 |
+| 10000x10000 | 2.692389                  | 0.6747584                 |
+| 20000x20000 | 10.67763                  | 2.615553                  |
+| 30000x30000 | 24.33534                  | 5.987761                  |
+
+```{r diagram}
+library(ggplot2)
+library(dplyr)
+library(tidyr)
+
+# prepare data
+data <- tribble(
+  ~Matrix.size, ~R.sum, ~C.sum,
+  "5", 7.152557e-06, 7.867813e-06,
+  "10", 9.775162e-06, 5.00679e-06,
+  "50", 9.346008e-05, 8.106232e-06,
+  "100", 0.0003376007, 1.955032e-05,
+  "500", 0.007472992, 0.001415014,
+  "1000", 0.03007007, 0.005748034,
+  "5000", 0.6559205, 0.1854615,
+  "10000", 2.692389, 0.6747584,
+  "20000", 10.67763, 2.615553,
+  "30000", 24.33534, 5.987761
+)
+
+# Convert Matrix.size to factor with desired order
+data$Matrix.size <- factor(data$Matrix.size, levels = data$Matrix.size)
+
+# rearrange data
+data_long <- data %>%
+  pivot_longer(cols = c(R.sum, C.sum),
+               names_to = "Method",
+               values_to = "Duration")
+
+# Create the plot
+ggplot(data_long, aes(x = Matrix.size, y = Duration, color = Method)) +
+  geom_point() +
+  scale_y_log10() +
+  labs(x = "Matrix Size", y = "Duration (seconds)", color = "Method") +
+  ggtitle("Calculation Time per (square) matrix size") +
+  theme_minimal()
+```
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diff --git a/w1/install_libs.R b/w1/install_libs.R
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+install.packages("rmarkdown")
+install.packages("ggplot2")
+install.packages("dplyr")
+install.packages("tidyr")
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diff --git a/w1/make_c.sh b/w1/make_c.sh
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+R CMD SHLIB mat.c
diff --git a/w1/mat.R b/w1/mat.R
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+dyn.load("mat.so")
+
+
+sum1 <- function(matrix) {
+    result <- 0
+    for (i in seq_len(nrow(matrix))) {
+        for (j in seq_len(ncol(matrix))) {
+            result <- result + matrix[i, j]
+        }
+    }
+    return(result)
+}
+
+sum2 <- function(matrix) {
+    nrow <- nrow(matrix)
+    ncol <- ncol(matrix)
+    result <- .C("c_sum_matrix", as.double(matrix), as.integer(nrow), as.integer(ncol), result = double(1))$result
+    return(result)
+}
diff --git a/w1/mat.c b/w1/mat.c
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+#include <R.h>
+#include <Rinternals.h>
+
+void c_sum_matrix(double *matrix, int *nrow, int *ncol, double *result) {
+    int i, j;
+    *result = 0.0;
+    for (i = 0; i < *nrow; i++) {
+        for (j = 0; j < *ncol; j++) {
+            *result += matrix[i * (*ncol) + j];
+        }
+    }
+}
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diff --git a/w1/mat_tests.R b/w1/mat_tests.R
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+source("mat.R")
+
+time <- function(f) {
+  start_time <- Sys.time()
+  val <- f()
+  end_time <- Sys.time()
+  print(end_time - start_time)
+  return(val)
+}
+
+sizes <- c(5, 10, 50, 100, 500, 1000, 5000, 10000, 20000, 30000)
+# sizes <- c(5, 10, 50, 100, 500, 1000, 5000, 10000)
+
+# warm up
+
+for (size in 30:50) {
+  m <- matrix(runif(size * size), nrow = size, ncol = size)
+  sum1(m)
+  sum2(m)
+}
+
+for (size in sizes) {
+  m <- matrix(runif(size * size), nrow = size, ncol = size)
+  
+  cat(sprintf("Matrix size: %dx%d\n", size, size))
+  cat("sum1 run duration: ")
+  time(function() sum1(m))
+  cat("sum2 run duration: ")
+  time(function() sum2(m))
+  cat("\n")
+}
+
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